CSR GRACE & GRACE-FO Dynamic Ocean Mascons RL06.2DO
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
RL06.2DO monthly mass anomaly grids from GRACE and GRACE-FO determined following CSR RL06.2 processing altered for Dynamic Ocean analysis. GAD-based regularization constraints are used over the Arctic Ocean. The mascon processing includes a specific handling of the major earthquakes in Japan and Andaman Bay, similar to what was done for the RL06.2EQ mascons (doi:10.18738/T8/ZE7DUD), with a model of the Earthquake signals removed from the mascons in those regions. Additionally a GRD model is computed using the mascon ocean mask and consistent with Tamisiea et al., 2010, (doi:10.1029/2009JC005687) and removed from the mascons. The Earthquake and GRD models are provided as a companion grids, but both signals are already corrected for in the RL06.2DO mascons. All grids are provided globally with a quarter degree sampling in longitude/latitude. Only the ocean mascons are reported. The land mascons are set to "-99999.0". The grids cover the GRACE and GRACE-FO period from 04/2002 to 05/2024
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.008 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.022 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it